NDR vs EDR: The Key Differences
Network Detection and Response (NDR) is an increasingly integral part of the cybersecurity toolkit: they offer in-depth visibility into a network’s internal activities, and uncover the packet contents flowing between devices. Endpoint Detection and Response (EDR), on the other hand, focuses entirely on uncovering the individual processes occurring within each of an organization’s endpoint devices.
While they rely on similar threat analysis and profiling mechanisms, their deployments and use cases are highly distinct. This article will cover the differences, and touch on how EDR and NDR are often deployed alongside one another.
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What is NDR?
NDR is a tool that monitors interactions between devices on an organization’s internal network. It deploys sensors across an organization’s networks, monitors which devices are interacting with it, and analyzes the data they’re sending to peers and external servers alike.
This may sound similar to a firewall: while a firewall analyzes traffic coming into or out of a network – called North-South traffic – it offers no visibility into the traffic between internal devices. NDRs allow for a network’s internal, or East-West traffic, to be monitored: it offers a new depth of network visibility, without heavy configuration demands.
The raw data gathered by NDR systems consists of the following:
- Raw network packets : Captured directly from network traffic via SPAN ports, TAPs, or dedicated sensors. These packets offer full transaction visibility, including protocol headers and payload-related metadata.
- Flow records : Metadata formats like NetFlow or IPFIX that summarize communication patterns, including source and destination IP addresses, port numbers, protocols, and byte counts.
- Traffic metadata : Derived from packet analysis, this includes session duration, communication frequency, behavioral patterns of devices, and data from application-layer protocols.
All of this data is then ingested into the NDR tool’s own analysis engine, and processed for signs of malicious traffic. To maximize the chance of successful threat detection, NDR employs two analysis strategies:
Signature-based Network Analysis
As each individual network datapoint is assembled into a time-series graph, the activities of individual devices can be mapped against known threats. Signature-based detection consolidates specific network-level attack behaviors into Indicators of Compromise (IoCs), which are stored on the NDR’s own database.
A signature refers to any identifiable attribute linked to a known cyberattack—this could be a snippet of code from a specific malware variant or a recognizable subject line from a phishing email. Signature-based detection tools scan network activity for these known patterns and trigger alerts when matches are found.
Monitoring IOCs is inherently reactive. When an IOC is detected, it typically indicates that a breach has already occurred. However, if the malicious activity is still ongoing, early detection of an IOC can play a crucial role in interrupting the attack, allowing for quicker containment and reducing potential damage to the organization.
Behavioral Network Analysis
Alongside signature-based detection, most NDRs also offer behavioral analysis. This ingests all data points, but instead of statically comparing them against an external risk database, it uses them to build a behavioral baseline.
This baseline represents normal activity: it lines up devices and users with their communication frequency, data volume, and protocol usage. Once these expected behavior patterns have been defined, NDR solutions can effectively identify deviations that could signal a potential threat. There could be discrepancies between expected and actual protocol behavior, and unusual application activity during off-hours. NDR can also integrate with other security tools, in order to gain an even fuller picture of an organization’s normal network activity.
Collectively, both behavioral and signature-based threat detection allow NDR to provide not just full East-West visibility – but full network-level threat detection.
What is EDR?
- Process execution data : Details of all running processes, including parent-child relationships, command-line arguments, and execution timestamps.
- File system change : File creations, modifications, deletions, and integrity checks (including file hashes and download sources).
- Registry modifications : Changes to Windows registry keys and configuration settings critical to system behavior.
- User Accounts : All user accounts that have logged in, both directly and remotely
- System configurations : Installed applications, service states, and security policy compliance data.
Like NDR sensors, EDR agents continuously stream raw data to a centralized platform, where machine learning models analyze it for anomalies like unauthorized process chains, suspicious network communications, or registry changes associated with known attack techniques.
EDR vs NDR: Different Use Cases
IoT Security
NDR sensors are often based on SPAN ports – these work by creating copies of each packet that passes through their network. These copies are then forwarded to the NDR’s monitoring tools: this process of copying packet intel, rather than forwarding all original packets to the analysis engine, prevents disturbance to the host network.
Alongside protecting sensitive networks, this setup allows for the network activities of Internet of Things (IoT) devices to be tracked and secured. IoTs are often too lightweight and numerous to have agents installed on them, making them a now-renowned security threat. Weak passwords, poor default settings, and a severe lack of device management options have made IoT devices immensely difficult to keep secure – but, because NDR tools capture all network communications – IoT’s East-West behavior can be monitored. Furthermore, since suspicious traffic between IoT devices and their wider network can be mapped to known threats, Mean Time to Respond is drastically accelerated.
Remote Employee Protection
EDR provides continuous monitoring, threat detection, and automated response capabilities directly at the endpoint. This is particularly important since remote endpoints can’t always be limited to specific networks and peripheral devices. Without this protection, hybrid employees risk becoming infection vectors when they connect remote devices back up to the organization’s networks.
Furthermore, when a security event is discovered on a remote device, EDR can initiate the responding playbook according to its surrounding factors. If a set of IoCs that indicate ransomware is found, for instance, it can isolate the affected devices before it spreads.
Lateral Movement Detection
NDR vs EDR: Differences At A Glance
|
Feature / Capability |
NDR |
EDR |
| Focus Area |
Monitors network traffic and communications. |
Monitors individual endpoint devices (e.g., laptops, servers). |
| Data Sources | Network packets, flow records (NetFlow/IPFIX), metadata. | System logs, file activity, process behavior, registry changes. |
| Visibility Scope | Broad, network-wide visibility. | Deep, device-level visibility. |
| Threat Detection Methods | Anomaly detection, behavioral analytics, encrypted traffic inspection. | File analysis, behavior monitoring, signature-based detection. |
| Use Cases | Lateral movement, command-and-control traffic, data exfiltration. | Malware infections, insider threats, exploit attempts. |
| Response Capabilities | Alerts and integrations with SIEM/SOAR; limited direct remediation. | Automated threat containment (e.g., process kill, device isolation). |
| Deployment Scenario | Enterprise networks with many connected devices. | Remote workforces, BYOD environments, high-risk endpoints. |
| Deployment Requirements | Typically agentless; uses network sensors such as taps and SPAN ports. | Requires agents installed on each monitored endpoint device. |
Integrate EDR with NDR via Stellar Cyber
Since the two tools operate in tandem so well, they’re often deployed together. This heightens the importance of each tool’s integration capabilities, as the intel gained from each can significantly accelerate MTTR. Stellar Cyber embodies this joint capability with its OpenXDR product – integrating with any EDR, it conducts Deep Packet Inspection (DPI) alongside malware sandboxing for always-on, zero day malware detection and prevention.
OpenXDR correlates network-level alerts with those generated by an organization’s own stack of security tools into accessible incidents. Rather than filling analysts’ workflows with endless alerts, Stellar proactively sorts and filters them into immediate action requirements. Explore how OpenXDR can give proactive response capabilities back to your security team with a demo today.
